Top Entry Level Jobs in Boston, MA

Provide phone and email technical support for Bevi beverage machines, troubleshooting routine and non-routine issues, guiding installations and maintenance, answering warranty and contract questions, initiating RMAs, and scheduling service calls. The role also identifies customer opportunities, supports sales inquiries, manages tickets, analyzes trends, and recommends process improvements to internal stakeholders and engineering teams.

Five-and-a-half-month applied AI and analytics co-op building production-ready AI solutions, data pipelines, dashboards, reports, models, and agentic workflow prototypes. The role involves analyzing messy datasets, identifying insights, automating analytical workflows, documenting prompts, and presenting recommendations to business stakeholders. Co-ops work on live enterprise projects and support SharkNinja’s AI transformation initiatives while collaborating with technical and business teams.

Analyze Marketing data to develop monitoring systems, standardized reports, and dashboards. Write SQL queries, support dbt models, investigate channel performance, conduct root cause analysis, communicate findings to non-technical stakeholders, track incidents, and support vendor and data infrastructure evaluations.

Design and implement software for prototypes and production applications within an agile engineering team. Collaborate with business, marketing, and UX partners; contribute to product ideation, rapid prototyping, data analysis, user interfaces, custom algorithms, and emerging technology experiments. Participate in hackathons, meetups, and technical learning opportunities while helping develop innovative insurance technology products.

Manage strategic lender accounts using the Reggora platform, build trusted-advisor relationships, advise on appraisal workflows, monitor account health and adoption, conduct quarterly business reviews, and identify expansion opportunities. The role requires customer success or account management experience, data analysis skills, technical aptitude, strong communication, and the ability to manage multiple priorities independently. Residential appraisal knowledge is preferred.

Own the end-to-end customer lifecycle for Robin’s B2B SaaS customers, including onboarding, relationship management, adoption, renewals, and expansion. Drive retention and revenue goals through account planning, usage analysis, executive business reviews, and advocacy development. Partner with Support, Product, Engineering, Sales, and Marketing to resolve issues, communicate roadmap value, and deliver customer feedback. Manage a multi-million-dollar book of national and multinational accounts.

Develop software solutions for Assurance client engagements, participating in architecture, design, coding, testing, maintenance, and code reviews. Collaborate with project teams to create scalable systems, apply computer science and engineering principles, interpret data, and provide technical insights. The role emphasizes learning, innovation, client service, teamwork, adaptability, and using AI and emerging technologies to improve financial reporting and decision-making processes.

Leads onsite service relationships for a New York Life general office, serving as liaison among agency managers, recruiters, agents, and service teams. Resolves escalations, oversees onsite specialists, supports sales initiatives, trains users on AI and digital tools, coordinates engagement events, drives adoption, manages office operations, and oversees financial processes.

Supports retail space planning through data analytics, performance reporting, and store layout optimization. Creates and validates Power BI dashboards and reporting tools, analyzes space productivity, maps data, and identifies actionable opportunities. Collaborates with Space Planning and Commercial Solutions teams while maintaining merchandising standards. The co-op combines business analytics, retail strategy, database concepts, data visualization, and emerging AI tools in a hybrid environment.

Supports data science teams by cleaning and processing structured and unstructured data, engineering features, executing and monitoring machine learning pipelines, generating insights, investigating trends and risks, and collaborating with senior data scientists and business analysts. The role requires a current MIT quantitative-field bachelor's student working 10–20 hours weekly in the continental United States.